A Visiting Research Fellowship at the University of Aizu

Job Purpose

To make a leading contribution to the NMM funded project “Improving multi-scale variability and interactions in a global coupled seasonal climate forecast system through embedded regional modeling at weather and cloud resolving scales”, working with Dr. Saji Hameed at University of Aizu and partners at the Indian Institute of Tropical Meteorology. Specifically the job requires expert knowledge in climate data analysis and modeling, and experience in working with diverse large climate and weather data sets and formats.

The candidate will explore the multiscale variations of the Indian summer monsoon rainfall (ISMR) in a coupled seasonal forecast system that is being developed for operational forecasts over India. The ISMR features exceptionally rich features in time and space resulting from the interaction of multiscale phenomenon ranging from monsoon lows and intraseasonal oscillations to low-frequency climate modes such as the Indian Ocean Dipole and El Nino Southern Oscillation. The candidate will use innovative analysis to unravel the interplay of these scales and evaluate their simulation in the coupled seasonal forecast system. S/he will also test the feasibility of using embedded regional climate modeling as a means of improving multiscale variations and interactions in the said coupled seasonal forecast system.

Main Duties and Responsibilities

Perform the following activities in conjunction with the Principal Investigator:

1. Take a leading role in the planning and conduct of the assigned research individually or jointly in accordance with the project deliverables and project/group research strategy.

2. Take a leading role in designing innovative analyses, including non linear techniques in support of the project objectives.

3. Take a leading role in implementing the Weather Research and Forecast (WRF) model and designing numerical experiments in support of the project objectives.

4. Document research output including analysis and interpretation of all data, maintaining records and databases, drafting technical/progress reports and papers as appropriate.

5. Survey the research literature and environment, understand the research challenges associated with the project and subject areas, and develop/implement a suitable research strategy.

6. Presentation of work at international and national conferences, at internal and external seminars, colloquia and workshops to develop and enhance our research profile.

7. Take a leading role in developing and maintaining collaborations with colleagues across the research group/university/partners and wider community.

8. Take a leading role in the organisation, supervision, mentoring and training of undergraduate and/or postgraduate students and less experienced members of the project team to ensure their effective development.

Knowledge, Qualifications, Skills and Experience


Essential Skills:

Desirable Skills:


Place of work: Aizuwakamatsu, Fukushima, Japan

Form of employment: The position is available up to two years, subject to satisfactory performance in the first year.

Starting date: The anticipated start date is Feb 1, 2014.The value of the fellowship corresponds to an annual salary of JPY 3,309,600. An additional annual sum of around JPY 507,600 will be paid towards social insurance and for commutation.

Application: We welcome your application marked with Ref no. NMM/PD

CV, publication list, PhD diploma, copies of no more than five publications. A short motivation letter (< 2 pages) outlining previous research, current research interests and other activities of relevance for the position. Names and addresses of at least two reference persons. All application documents should be written in English.

Please submit your application to saji@u-aizu.ac.jp preferably by 15 January, 2014.

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About the National Monsoon Mission (NMM) project

Prediction of monsoon rainfall variability in all spatial and time scales is very important for many sectors like agriculture, water resources management, power generation and natural ecosystems and thus economy of the country. The present statistical methods being used for forecasting the Indian Monsoon rainfall have some constraints to meet specific user requirements for forecasts on finer spatial and temporal scale. Therefore, it is necessary to make use of the state of the art dynamic models to improve monsoon prediction skills.

The main objectives of the National Monsoon Mission are:

(i) To build a working partnership between the academic and R&D organisations both national and international and the operational agencies to improve the operational monsoon forecast skill over the country.

(ii) To set up a state of the art dynamic modelling framework for improving the prediction skill of:

a. Seasonal and extended range prediction system (16 days to one season)

b. Short to medium range prediction system (up to 15 days).

The National Monsoon Mission after its implementation will help to implement a dynamic prediction system for the prediction of monsoon in all time scales, short range to seasonal time scale at appropriate spatial scales with improved prediction skill. The forecasts based on this prediction system will cater to the needs of various sectors like agriculture, water resources management, power generation, disaster management, tourism and transport.

The programme will be undertaken through two sub-missions on two different time scales, (i) extended range to seasonal time scale to be coordinated by the Indian Institute of Tropical Meteorology (IITM) Pune/ESSO and (ii) short to medium range scale, to be coordinated by the National Centre for Medium Range Weather Forecasting (NCMRWF)/ESSO. The Indian National Center for Ocean Information Services (INCOIS)/ESSO will provide the ocean observations for assimilation and the India Meteorological Department/ESSO will implement the research outcome of the efforts in operational mode. The Mission will support focused research by national and international research groups with definitive objectives and deliverables to improve the models in the short, medium, extended and seasonal range scales at appropriate spatial scales. The Mission will also support observational programmes that will result in better understanding of the processes.

Further details are available here and here